COVID-19 is commonly mild and self-limiting, but in a considerable portion of patients the disease is severe and fatal. Determining which patients are at high risk of severe illness or mortality is essential for appropriate clinical decision making. We propose a novel severity score specifically for COVID-19 to help predict disease severity and mortality. 4711 patients with confirmed SARS-CoV-2 infection were included. We derived a risk model using the first half of the cohort (n = 2355 patients) by logistic regression and bootstrapping methods. The discriminative power of the risk model was assessed by calculating the area under the receiver operating characteristic curves (AUC). The severity score was validated in a second half of 2356 patients. Mortality incidence was 26.4% in the derivation cohort and 22.4% in the validation cohort. A COVID-19 severity score ranging from 0 to 10, consisting of age, oxygen saturation, mean arterial pressure, blood urea nitrogen, C-Reactive protein, and the international normalized ratio was developed. A ROC curve analysis was performed in the derivation cohort achieved an AUC of 0.824 (95% CI 0.814–0.851) and an AUC of 0.798 (95% CI 0.789–0.818) in the validation cohort. Furthermore, based on the risk categorization the probability of mortality was 11.8%, 39% and 78% for patient with low (0–3), moderate (4–6) and high (7–10) COVID-19 severity score. This developed and validated novel COVID-19 severity score will aid physicians in predicting mortality during surge periods.

Objective:The SARS-Cov2 virus is protean in its manifestations, affecting nearly every organ system. However, nervous system involvement and its impact on disease outcome are poorly characterized. The objective of the study is to determine if neurological syndromes are associated with increased risk of inpatient mortality.Methods:581 hospitalized patients with confirmed SARS-Cov2 infection, neurological involvement and brain-imaging were compared to hospitalized non-neurological COVID-19 patients. Four patterns of neurological manifestations were identified –acute stroke, new or recrudescent seizures, altered mentation with normal imaging, and neuro-COVID-19 complex. Factors present on admission were analyzed as potential predictors of in-hospital mortality, including sociodemographic variables, pre-existing comorbidities, vital-signs, laboratory values, and pattern of neurological manifestations. Significant predictors were incorporated into a disease-severity score. Patients with neurological manifestations were matched with patients of the same age and disease severity to assess the risk of death.Results:4711 patients with confirmed SARS-Cov2 infection were admitted to one medical system in New York City during a 6-week period. Of these, 581 (12%) had neurological issues of sufficient concern to warrant neuro-imaging. These patients were compared to 1743 non-neurological COVID-19 patients matched for age and disease-severity admitted during the same period. Patients with altered mentation (n=258, p =0.04, OR 1.39, CI 1.04 – 1.86) or radiologically confirmed stroke (n=55, p = 0.001, OR 3.1, CI 1.65-5.92) had a higher risk of mortality than age and severity-matched controls.Conclusions:The incidence of altered mentation or stroke on admission predicts a modest but significantly higher risk of in-hospital mortality independent of disease severity. While other biomarker factors also predict mortality, measures to identify and treat such patients may be important in reducing overall mortality of COVID-19.

Objective We aim to characterize the incidence, risk for mortality, and identify risk factors for mortality in patients presenting with hemorrhage and COVID-19. Methods This retrospective cohort study included a cohort of patients admitted to one of three major hospitals of our healthcare network including, an academic medical center and comprehensive stroke center, which accepts transfers for complex cases from eight community hospitals, during March 1 to May 1, 2020. All patients that received imaging of the neuroaxis and had positive PCR testing for COVID-19 were identified and reviewed by an attending neuroradiologist. Demographics and comorbidities were recorded. Biomarkers were recorded from the day of the hemorrhagic event. Vital signs from the day of the hemorrhagic event mechanical ventilation orders at admission were recorded. Imaging findings were divided into 5 subtypes; acute subdural hematoma (SDH), subarachnoid hemorrhage (SAH), multi-compartmental hemorrhage (MCH), multi-focal intracerebral hemorrhage (MFH), and focal intracerebral hemorrhage (fICH). Outcomes were recorded as non-routine discharge and mortality. Results We found a total of 35 out of 5227 patients with COVID-19 that had hemorrhage of some kind. Mortality for the entire cohort was 45.7 % (n = 16). SDH patients had a mortality rate of 35.3 % (n = 6), SAH had a mortality of 50 % (n = 1), MCH patients had a mortality of 71.4 % (n = 5), MFH patients had a mortality of 50 % (n = 2), fICH patients had a mortality of 40 % (n = 2). Patients with severe pulmonary COVID requiring mechanical ventilation (OR 10.24 [.43−243.12] p = 0.015), with INR > 1.2 on the day of the hemorrhagic event (OR 14.36 [1.69−122.14] p = 0.015], and patients presenting with spontaneous vs. traumatic hemorrhage (OR 6.11 [.31−118.89] p = 0.023) had significantly higher risk for mortality. Conclusions Hemorrhagic presentations with COVID-19 are a rare but serious way in which the illness can manifest. It is important for neurosurgeons to realize that patients can present with these findings without primary pulmonary symptoms, and that severe pulmonary symptoms, elevated INR, and spontaneous hemorrhagic presentations is associated with increased risk for mortality.

IntroductionCOVID-19 is commonly mild and self-limiting, but in a considerable portion of patients the disease is severe and fatal. Determining which patients are at high risk of severe illness or mortality is essential for appropriate clinical decision making. We propose a novel severity score specifically for COVID-19 to help predict disease severity and mortality.Methods4,711 patients with confirmed SARS-CoV-2 infection were included. We derived a risk model using the first half of the cohort (n=2,355 patients) by logistic regression and bootstrapping methods. The discriminative power of the risk model was assessed by calculating the area under the receiver operating characteristic curves (AUC). The severity score was validated in a second half of 2,356 patients.ResultsMortality incidence was 26.4% in the derivation cohort and 22.4% in the validation cohort. A COVID-19 severity score ranging from 0 to 10, consisting of age, oxygen saturation, mean arterial pressure, blood urea nitrogen, C-Reactive protein, and the international normalized ratio was developed. A ROC curve analysis was performed in the derivation cohort achieved an AUC of 0.824 (95% CI 0.814-0.851) and an AUC of 0.798 (95% CI 0.789-0.818) in the validation cohort. Furthermore, based on the risk categorization the probability of mortality was 11.8%, 39% and 78% for patient with low (0-3), moderate (4-6) and high (7-10) COVID-19 severity score.ConclusionThis developed and validated novel COVID-19 severity score will aid physicians in predicting mortality during surge periods.

BACKGROUND AND PURPOSE: Our hypothesis is that the COVID-19 pandemic led to delayed presentations for patients with acute ischemic stroke. This study evaluates the impact of the coronavirus disease 2019 pandemic on presentation, treatment, and outcomes of patients with emergent large-vessel occlusion using data from a large health system in the Bronx, New York. MATERIALS AND METHODS: We performed a retrospective cohort study of 2 cohorts of consecutive patients with emergent large-vessel occlusion admitted to 3 Montefiore Health System hospitals in the Bronx from January 1 to February 17, 2020, (prepandemic) and March 1 to April 17, 2020 (pandemic). We abstracted data from the electronic health records on presenting biomarker profiles, admission and postprocedural NIHSS scores, time of symptom onset, time of hospital presentation, time of start of the thrombectomy procedure, time of revascularization, presenting ASPECTS, TICI recanalization score, mRS, functional outcomes, and mortality. RESULTS: Of 179 patients admitted with ischemic stroke during the study periods, 80 had emergent large-vessel occlusion, of whom 36 were in the pandemic group. Patients in the pandemic group were younger (66 versus 72 years, P , .061) and had lower ASPECTS (7 versus 9, P , .001) and took longer to arrive at the hospital (361 versus 152 minutes, P , .004) with no other major differences. There was a decreased rate of thrombolysis administration (22% versus 43%, P , .049) and a decreased number of patients treated with mechanical thrombectomy (33% versus 61%, P , .013). CONCLUSIONS: The pandemic led to delays in patients arriving at hospitals, leading to decreased patients eligible for treatment, while in-hospital evaluation and treatment times remain unchanged.

Background This study evaluates the mortality risk of patients with emergent large vessel occlusion (ELVO) and COVID-19 during the pandemic. Methods We performed a retrospective cohort study of two cohorts of consecutive patients with ELVO admitted to a quaternary hospital from March 1 to April 17, 2020. We abstracted data from electronic health records on baseline, biomarker profiles, key time points, quality measures and radiographic data. Results Of 179 patients admitted with ischemic stroke, 36 had ELVO. Patients with COVID-19 and ELVO had a higher risk of mortality during the pandemic versus patients without COVID-19 (OR 16.63, p = 0.004). An age-based sub-analysis showed in-hospital mortality in 60% of COVID-19 positive patients between 61-70 years-old, 66.7% in between 51-60 years-old, 50% in between 41-50 years-old and 33.3% in between 31-40 years old. Patients that presented with pulmonary symptoms at time of stroke presentation had 71.4% mortality rate. 27.3% of COVID-19 patients presenting with ELVO had a good outcome at discharge (mRS 0-2). Patients with a history of cigarette smoking (p = 0.003), elevated d-dimer (p = 0.007), failure to recanalize (p = 0.007), and elevated ferritin levels (p = 0.006) had an increased risk of mortality. Conclusion Patients with COVID-19 and ELVO had a significantly higher risk for mortality compared to COVID-19 negative patients with ELVO. A small percentage of COVID-19 ELVO patients had good outcomes. Age greater than 60 and pulmonary symptoms at presentation have higher risk for mortality. Other risk factors for mortality were a history of cigarette smoking, elevated, failure to recanalize, elevated d-dimer and ferritin levels.

Background: In recent years, the role of ABO blood type moved into focus through the discovery of different hemostaseologic properties with importance in many diseases including subarachnoid hemorrhage (SAH). However, the role of ABO blood type in delayed cerebral ischemia (DCI) onset, clinical progress, and outcome after SAH is to date largely unexplored. Our aim was to explore the role of ABO blood group in DCI and clinical outcomes after aneurysmal SAH (aSAH). Methods: A retrospective analysis was made with data collected from patients who presented aSAH at our single- academic center from 2015 to 2018. We included demographic, clinical, and imaging variables in the univariate analysis and in the subsequent multivariate analysis. Results: A total of 204 patients were included in this study. About 17.9% of “O” type patients developed a DCI while DCI was reported in only 8.2% of non-O type patients (P = 0.04). “O” type was an independent risk after in the logistic regression after adjusting for significant factors in the univariate analysis (OR=2.530, 95% CI: 1.040- 6.151, P = 0.41). Compared to “non-O” type patients, “O” type patients had a trend to have poorer outcomes at discharge (25.5% vs. 21.3%, P = 0.489) and at 12–18 months (21.1% vs. 19.5%, P = 0.795). However, there were no significant differences. Conclusion: Our study evidenced that patients with “O” blood type have higher risk of DCI onset after aSAH. Although these findings need to be confirmed, they may aid to improve DCI prevention and outcome predictions.

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